Spurious correlation #2,003 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Butter consumption and the second variable is Novo Nordisk's stock price (NVO). The chart goes from 2002 to 2021, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Butter consumption and the second variable is Novo Nordisk's stock price (NVO). The chart goes from 2002 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As butter consumption increased, people's taste for rich, indulgent foods also increased. This led to a higher demand for insulin and other diabetes medications produced by Novo Nordisk, driving up the company's stock price. It's a sweet and savory relationship between butter and Big Pharma's profits! Remember, this is all in good fun!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate a visually striking pop art-inspired scene of a person in bold, vibrant colors spreading a thick layer of butter on a slice of toast. The background should feature a simple, eye-catching depiction of a chart representing Novo Nordisk's stock price steadily rising, using contrasting colors and graphic shapes to convey the upward trend. The overall composition should feel dynamic and visually engaging in a pop art style. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Butter consumption and Novo Nordisk's stock price. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Cutsy art illustration An image that looks like it is a scene from A Disney Movie 3D Pixar Style Pop art Celtic art
ChatGPT: Pop art

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Butter consumption and Novo Nordisk's stock price together. Keep the description simple.
ChatGPT: A person spreading a thick layer of butter on a slice of toast, while a chart of Novo Nordisk's stock price steadily rises in the background.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ Pop art ] and depicting this scene: A person spreading a thick layer of butter on a slice of toast, while a chart of Novo Nordisk's stock price steadily rises in the background. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate a visually striking pop art-inspired scene of a person in bold, vibrant colors spreading a thick layer of butter on a slice of toast. The background should feature a simple, eye-catching depiction of a chart representing Novo Nordisk's stock price steadily rising, using contrasting colors and graphic shapes to convey the upward trend. The overall composition should feel dynamic and visually engaging in a pop art style.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Butter consumption caused Novo Nordisk's stock price (NVO) to increase.

AI academic paper

(Because p < 0.01)

Spreadin' Butter, Movin' the Market: Exploring the Correlation Between Butter Consumption and Novo Nordisk's Stock Price

The Journal of Gastronomic Economics and Financial Impacts

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Butter consumption and Novo Nordisk's stock price. Make lots of jokes, goofy observations, and puns.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
"Spreadin' Butter, Movin' the Market: Exploring the Correlation Between Butter Consumption and Novo Nordisk's Stock Price"

[[ABSTRACT]]
This paper delves into the surprisingly strong connection between the consumption of butter and the fluctuations of Novo Nordisk's stock price. While the notion may initially seem as slippery as a pat of butter, our research team has churned out some intriguing findings to spread before you. Utilizing data from the USDA and LSEG Analytics (Refinitiv), we conducted a thorough examination spanning from 2002 to 2021. The resulting correlation coefficient of 0.9508434 and a statistically significant p-value of less than 0.01 have raised quite a stir in the academic and financial communities. Our study leaves no stone unturned as it uncovers the buttery secret behind the movements of Novo Nordisk's stock price, shedding light on the often-overlooked influence of food trends on the stock market. So, grab your popcorn – or should we say, your buttered popcorn – and prepare to be surprised by the untold connection between a breakfast spread and stock market bread.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The world of finance is often regarded as a realm of numbers, algorithms, and stoic investor behavior. However, our research seeks to melt away this perception by delving into the unexpected and slightly whimsical relationship between butter consumption and Novo Nordisk's stock price. As we embark on this endeavor, it is crucial to acknowledge the lighthearted nature of exploring a connection that may initially seem as mismatched as spreading butter on a hot pancake.
The correlation between food consumption and financial markets has been a topic of interest for both economists and nutritionists, yet the specific focus on butter and its impact on a pharmaceutical company's stock price has not been previously unboxed. Just as the act of churning butter transforms cream into a spreadable delight, our research aims to unearth the hidden forces at play in the market dynamics surrounding Novo Nordisk, popularly known for its diabetes medications.
While some may dismiss our topic as being as inconsequential as the caloric content of a pat of butter, we refuse to let this topic be overlooked. Our investigation has yielded results that are as intriguing and complex as the intricate latticework on a croissant, challenging conventional wisdom in both the financial and culinary spheres. As we present our findings, allow us to butter you up with some deliciously surprising insights into the unexpected link between pantry staples and stock market performances.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The interplay between butter consumption and stock market performances has seldom been explored in academic literature. However, a few outliers have dared to delve into this quirky intersection. Smith (2015) observed a potential correlation between dairy product consumption and consumer spending behavior, laying a modest foundation for our current investigation. Meanwhile, Doe et al. (2018) conducted a comprehensive analysis of food trends and their impact on the stock market, inadvertently buttering up the path for our research.

Moving past the crème de la crème of academic studies, our inquiry also draws inspiration from publications outside the traditional financial realm. In "Dairy Delights: The Cultural History of Butter" (Jones, 2009), a rich exploration of butter's cultural significance provides a nuanced backdrop for understanding its potential influence on economic activities.

Turning the page to more unconventional sources, the fictional works of "The Butter Conspiracy" by the enigmatic author X. Butterman (2017) and "The Margarine Murmurs" by Y. Spreaderson (2014) offer an intriguing blend of conspiracy theories and culinary curiosities that surprisingly resonate with our research theme.

Yet, in the age of internet culture, it would be remiss not to acknowledge the impact of viral trends on contemporary discourse. The "Butter Dance" meme and the infamous "Buttergate" have permeated online spaces, amplifying the public's fascination with butter-related phenomena and reinforcing the idea that butter holds a unique sway over societal narratives.

As we navigate through this rather unorthodox amalgamation of sources, it becomes evident that our research occupies a distinctive and, dare we say, spreadable niche within the academic landscape.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Butter consumption and Novo Nordisk's stock price. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from USDA and LSEG Analytics (Refinitiv) . You used data from 2002 to 2021

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Spreadin' Butter, Movin' the Market: Exploring the Correlation Between Butter Consumption and Novo Nordisk's Stock Price"

[[ABSTRACT]]
This paper delves into the surprisingly strong connection between the consumption of butter and the fluctuations of Novo Nordisk's stock price. While the notion may initially seem as slippery as a pat of butter, our research team has churned out some intriguing findings to spread before you. Utilizing data from the USDA and LSEG Analytics (Refinitiv), we conducted a thorough examination spanning from 2002 to 2021. The resulting correlation coefficient of 0.9508434 and a statistically significant p-value of less than 0.01 have raised quite a stir in the academic and financial communities. Our study leaves no stone unturned as it uncovers the buttery secret behind the movements of Novo Nordisk's stock price, shedding light on the often-overlooked influence of food trends on the stock market. So, grab your popcorn – or should we say, your buttered popcorn – and prepare to be surprised by the untold connection between a breakfast spread and stock market bread.

[[INTRODUCTION]]
The world of finance is often regarded as a realm of numbers, algorithms, and stoic investor behavior. However, our research seeks to melt away this perception by delving into the unexpected and slightly whimsical relationship between butter consumption and Novo Nordisk's stock price. As we embark on this endeavor, it is crucial to acknowledge the lighthearted nature of exploring a connection that may initially seem as mismatched as spreading butter on a hot pancake.
The correlation between food consumption and financial markets has been a topic of interest for both economists and nutritionists, yet the specific focus on butter and its impact on a pharmaceutical company's stock price has not been previously unboxed. Just as the act of churning butter transforms cream into a spreadable delight, our research aims to unearth the hidden forces at play in the market dynamics surrounding Novo Nordisk, popularly known for its diabetes medications.
While some may dismiss our topic as being as inconsequential as the caloric content of a pat of butter, we refuse to let this topic be overlooked. Our investigation has yielded results that are as intriguing and complex as the intricate latticework on a croissant, challenging conventional wisdom in both the financial and culinary spheres. As we present our findings, allow us to butter you up with some deliciously surprising insights into the unexpected link between pantry staples and stock market performances.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To unearth the buttery secrets behind Novo Nordisk's stock price movements, our research team employed a multi-faceted methodology, as complex and interwoven as the layers of a flaky croissant. We first curated data on butter consumption from the USDA, scouring through decades of statistics as meticulously as a baker sifting flour. Utilizing LSEG Analytics (Refinitiv), we then gathered daily stock price data for Novo Nordisk, tracking the company's market performance with the precision of a master chef measuring ingredients.

To establish the relationship between butter consumption and Novo Nordisk's stock price, we indulged in a statistical feast, commencing with a series of descriptive analyses. We scrutinized the consumption trends of butter, examining both the annual per capita consumption and the seasonal variations to capture the ebb and flow of culinary preferences. In parallel, we dived into the daily fluctuations of Novo Nordisk's stock price, detecting patterns and trends with the keen eye of a seasoned sommelier discerning the nuances of a fine wine.

With the data on hand, we tenderly whipped up a delectable dish of correlation analysis. Employing the Pearson correlation coefficient, we measured the strength and direction of the linear relationship between butter consumption and Novo Nordisk's stock price, as meticulously as a pastry chef crafting the perfect meringue. We then subjected our findings to rigorous hypothesis testing, where the null hypothesis dared to claim that there was no association between butter consumption and Novo Nordisk's stock price – a claim surely as bold as substituting butter with margarine in a classic recipe.

In our pursuit of accuracy, we also conducted a time series analysis, embracing the complexities of temporal dynamics with the same fervor as a chef layering butter in a delicate puff pastry. By applying sophisticated econometric techniques, we sought to unravel the temporal patterns and potential lag effects, recognizing that the impact of butter consumption on stock price may unfold gradually, much like the slow melting of butter on a warm slice of toast.

Throughout this process, we remained vigilant for potential confounding variables that could churn our conclusions, ensuring that our analysis captured the true essence of the butter-stock price relationship. Finally, we engaged in a validation process, akin to a panel of discerning taste-testers, to confirm the robustness of our findings and ensure that they were more reliable than a butter substitute in a soufflé.

In sum, our methodology represents a harmonious blend of culinary finesse and financial acumen, culminating in a rich, flavorful understanding of the interconnectedness between butter consumption and Novo Nordisk's stock price. Like the perfect fusion of a decadent butter sauce and a succulent dish, our methodology entwines empirical rigor with a dash of whimsy, offering a palatable and nourishing exploration into the unexpected flavors of financial research.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Butter consumption and Novo Nordisk's stock price. Make lots of jokes, goofy observations, and puns.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
"Spreadin' Butter, Movin' the Market: Exploring the Correlation Between Butter Consumption and Novo Nordisk's Stock Price"

[[ABSTRACT]]
This paper delves into the surprisingly strong connection between the consumption of butter and the fluctuations of Novo Nordisk's stock price. While the notion may initially seem as slippery as a pat of butter, our research team has churned out some intriguing findings to spread before you. Utilizing data from the USDA and LSEG Analytics (Refinitiv), we conducted a thorough examination spanning from 2002 to 2021. The resulting correlation coefficient of 0.9508434 and a statistically significant p-value of less than 0.01 have raised quite a stir in the academic and financial communities. Our study leaves no stone unturned as it uncovers the buttery secret behind the movements of Novo Nordisk's stock price, shedding light on the often-overlooked influence of food trends on the stock market. So, grab your popcorn – or should we say, your buttered popcorn – and prepare to be surprised by the untold connection between a breakfast spread and stock market bread.

[[LITERATURE REVIEW]]
The interplay between butter consumption and stock market performances has seldom been explored in academic literature. However, a few outliers have dared to delve into this quirky intersection. Smith (2015) observed a potential correlation between dairy product consumption and consumer spending behavior, laying a modest foundation for our current investigation. Meanwhile, Doe et al. (2018) conducted a comprehensive analysis of food trends and their impact on the stock market, inadvertently buttering up the path for our research.
Moving past the crème de la crème of academic studies, our inquiry also draws inspiration from publications outside the traditional financial realm. In "Dairy Delights: The Cultural History of Butter" (Jones, 2009), a rich exploration of butter's cultural significance provides a nuanced backdrop for understanding its potential influence on economic activities.
Turning the page to more unconventional sources, the fictional works of "The Butter Conspiracy" by the enigmatic author X. Butterman (2017) and "The Margarine Murmurs" by Y. Spreaderson (2014) offer an intriguing blend of conspiracy theories and culinary curiosities that surprisingly resonate with our research theme.
Yet, in the age of internet culture, it would be remiss not to acknowledge the impact of viral trends on contemporary discourse. The "Butter Dance" meme and the infamous "Buttergate" have permeated online spaces, amplifying the public's fascination with butter-related phenomena and reinforcing the idea that butter holds a unique sway over societal narratives.
As we navigate through this rather unorthodox amalgamation of sources, it becomes evident that our research occupies a distinctive and, dare we say, spreadable niche within the academic landscape.

[[RESULTS]]
The analysis of the data collected from the USDA and LSEG Analytics (Refinitiv) has yielded some truly buttery results. The correlation coefficient between butter consumption and Novo Nordisk's stock price from 2002 to 2021 was calculated to be 0.9508434, indicating a strong positive relationship between these seemingly unrelated variables. This correlation is as strong as the aroma of freshly baked croissants wafting through a Parisian bakery!
Furthermore, the r-squared value of 0.9041032 suggests that a substantial 90.4% of the variance in Novo Nordisk's stock price can be explained by changes in butter consumption. It seems that the market movements of this pharmaceutical company are not so much about sugar pills but rather the spreading of a luscious layer of butter.
The statistical significance of this relationship is confirmed by a p-value of less than 0.01, indicating that the likelihood of observing such a strong correlation by chance alone is as improbable as finding a pat of butter in a vegan's fridge.
As a visual representation of our findings, we present Figure 1, a scatterplot illustrating the robust correlation between butter consumption and Novo Nordisk's stock price. This graph is set to churn the tides of conventional financial wisdom, serving as a visual reminder that the stock market, much like a sandwich, can be influenced by what's spread inside.
In conclusion, our investigation has successfully highlighted the surprising influence of butter consumption on the stock price of Novo Nordisk. These findings may encourage investors to ponder whether they should consider the spreadability of butter alongside other financial indicators. After all, a pat of butter might just be the unsung hero in predicting market trends.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our findings have churned up a veritable cornucopia of food for thought, reinforcing the existing literature's whispers of a mysterious connection between butter consumption and stock market movements. It's clear that the buttery allure extends beyond culinary realms to leave a rich, albeit creamy, mark on financial landscapes. The robust positive correlation observed in our study aligns with the modest groundwork laid by Smith in 2015 and Doe et al. in 2018, suggesting that butter's influence on consumer spending behavior may ripple through to stock prices. While some may have initially dismissed these previous studies as mere flights of fancy, our results have validated their claims, demonstrating that the butter-stock relationship is as solid as a stick of unsalted butter left out at room temperature.

Taking a more nuanced perspective, our study not only fits snugly into the financial literature but also draws inspiration from unconventional sources. The cultural insights from Jones's "Dairy Delights" provide a creamy backdrop for understanding butter's subtle but significant impact on economic activities. Furthermore, the seemingly whimsical conspiracy theories of X. Butterman and Y. Spreaderson surprisingly resonate with our findings. Who would have thought that these seemingly outlandish narratives would find a place in the annals of serious academic research? The metaphorical plot thickens like a buttery béchamel sauce, adding layers of intrigue to our understanding of this unconventional yet impactful relationship.

Our results also bring to light the potential implications for investors. With butter consumption serving as more than just a condiment for one's morning toast, investors might now find themselves pondering the inclusion of butter consumption trends in their financial predictions. Perhaps it's time to spread their investment portfolios to include this previously overlooked factor. After all, a pat of butter might just hold the key to understanding market fluctuations – a seemingly unexpected ally in the world of finance.

In conclusion, our study's findings have created quite the stir, reaffirming the notion that the butter-stocked relationship is indeed a potent force to be reckoned with. As the aroma of freshly baked croissants wafts through the air, we are reminded that the financial world, much like a well-baked pastry, can be influenced by the humble spread of butter. This study opens up a whole new avenue of exploration, challenging traditional financial wisdom to embrace the unassuming influence of food trends in shaping market dynamics. So, to the skeptics out there, "butter" believe it – the butter-stock connection is no mere flight of fancy but a deliciously significant phenomenon worthy of further investigation.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Butter consumption and Novo Nordisk's stock price. Make lots of jokes, goofy observations, and puns.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Spreadin' Butter, Movin' the Market: Exploring the Correlation Between Butter Consumption and Novo Nordisk's Stock Price"

[[ABSTRACT]]
This paper delves into the surprisingly strong connection between the consumption of butter and the fluctuations of Novo Nordisk's stock price. While the notion may initially seem as slippery as a pat of butter, our research team has churned out some intriguing findings to spread before you. Utilizing data from the USDA and LSEG Analytics (Refinitiv), we conducted a thorough examination spanning from 2002 to 2021. The resulting correlation coefficient of 0.9508434 and a statistically significant p-value of less than 0.01 have raised quite a stir in the academic and financial communities. Our study leaves no stone unturned as it uncovers the buttery secret behind the movements of Novo Nordisk's stock price, shedding light on the often-overlooked influence of food trends on the stock market. So, grab your popcorn – or should we say, your buttered popcorn – and prepare to be surprised by the untold connection between a breakfast spread and stock market bread.

[[INTRDUCTION]]
The world of finance is often regarded as a realm of numbers, algorithms, and stoic investor behavior. However, our research seeks to melt away this perception by delving into the unexpected and slightly whimsical relationship between butter consumption and Novo Nordisk's stock price. As we embark on this endeavor, it is crucial to acknowledge the lighthearted nature of exploring a connection that may initially seem as mismatched as spreading butter on a hot pancake.
The correlation between food consumption and financial markets has been a topic of interest for both economists and nutritionists, yet the specific focus on butter and its impact on a pharmaceutical company's stock price has not been previously unboxed. Just as the act of churning butter transforms cream into a spreadable delight, our research aims to unearth the hidden forces at play in the market dynamics surrounding Novo Nordisk, popularly known for its diabetes medications.
While some may dismiss our topic as being as inconsequential as the caloric content of a pat of butter, we refuse to let this topic be overlooked. Our investigation has yielded results that are as intriguing and complex as the intricate latticework on a croissant, challenging conventional wisdom in both the financial and culinary spheres. As we present our findings, allow us to butter you up with some deliciously surprising insights into the unexpected link between pantry staples and stock market performances.

[[RESULTS]]
The analysis of the data collected from the USDA and LSEG Analytics (Refinitiv) has yielded some truly buttery results. The correlation coefficient between butter consumption and Novo Nordisk's stock price from 2002 to 2021 was calculated to be 0.9508434, indicating a strong positive relationship between these seemingly unrelated variables. This correlation is as strong as the aroma of freshly baked croissants wafting through a Parisian bakery!
Furthermore, the r-squared value of 0.9041032 suggests that a substantial 90.4% of the variance in Novo Nordisk's stock price can be explained by changes in butter consumption. It seems that the market movements of this pharmaceutical company are not so much about sugar pills but rather the spreading of a luscious layer of butter.
The statistical significance of this relationship is confirmed by a p-value of less than 0.01, indicating that the likelihood of observing such a strong correlation by chance alone is as improbable as finding a pat of butter in a vegan's fridge.
As a visual representation of our findings, we present Figure 1, a scatterplot illustrating the robust correlation between butter consumption and Novo Nordisk's stock price. This graph is set to churn the tides of conventional financial wisdom, serving as a visual reminder that the stock market, much like a sandwich, can be influenced by what's spread inside.
In conclusion, our investigation has successfully highlighted the surprising influence of butter consumption on the stock price of Novo Nordisk. These findings may encourage investors to ponder whether they should consider the spreadability of butter alongside other financial indicators. After all, a pat of butter might just be the unsung hero in predicting market trends.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has uncovered a delightfully rich and creamy correlation between butter consumption and Novo Nordisk's stock price. This unexpected link may leave some scratching their heads, much like trying to discern margarine from butter in a blind taste test. Our findings suggest that the ebb and flow of stock prices may be as influenced by breakfast spreads as they are by economic indicators.

Our study has undoubtedly churned up quite a bit of commotion, much like the vigorous shaking of a jar to make homemade butter. The statistical significance of the relationship between butter consumption and Novo Nordisk's stock price is as clear as the golden hue of clarified butter.

While some may be tempted to dismiss the significance of our findings, we encourage readers to embrace the unexpected and recognize that the market, much like a batch of artisanal butter, can surprise even the most seasoned observers.

In light of these findings, we assert that no further research is necessary in this area. It's time to butter off and spread our newfound knowledge to the financial and culinary worlds alike. After all, there's no need to churn up any more investigations – we've already buttered our bread with these findings.

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited Spreadin' Butter, Movin' the Market: Exploring the Correlation Between Butter Consumption and Novo Nordisk's Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Gastronomic Economics and Financial Impacts

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Spreadin' Butter, Movin' the Market: Exploring the Correlation Between Butter Consumption and Novo Nordisk's Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Institute of Butter Economics and Stock Market Dynamics

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Spreadin' Butter, Movin' the Market: Exploring the Correlation Between Butter Consumption and Novo Nordisk's Stock Price with an abstract of This paper delves into the surprisingly strong connection between the consumption of butter and the fluctuations of Novo Nordisk's stock price. While the notion may initially seem as slippery as a pat of butter, our research team has churned out some intriguing findings to spread before you. Utilizing data from the USDA and LSEG Analytics (Refinitiv), we conducted a thorough examination spanning from 2002 to 2021. The resulting correlation coefficient of 0.9508434 and a statistically significant p-value of less than 0.01 have raised quite a stir in the academic and financial communities. Our study leaves no stone unturned as it uncovers the buttery secret behind the movements of Novo Nordisk's stock price, shedding light on the often-overlooked influence of food trends on the stock market. So, grab your popcorn – or should we say, your buttered popcorn – and prepare to be surprised by the untold connection between a breakfast spread and stock market bread.

ChatGPT:

Butter consumption, Novo Nordisk, stock price, correlation, USDA data, LSEG Analytics, Refinitiv, food trends, stock market, correlation coefficient, p-value, financial trends, market analysis, food industry, financial impact

*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.

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Data details

Butter consumption
Detailed data title: Per capita consumption of Butter in the US
Source: USDA
See what else correlates with Butter consumption

Novo Nordisk's stock price (NVO)
Detailed data title: Opening price of Novo Nordisk (NVO) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: ^{See full details} Via Microsoft Excel Stockhistory function

See what else correlates with Novo Nordisk's stock price (NVO)

Correlation r = 0.9508434 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r² = 0.9041032 (Coefficient of determination)
This means 90.4% of the change in the one variable (i.e., Novo Nordisk's stock price (NVO)) is predictable based on the change in the other (i.e., Butter consumption) over the 20 years from 2002 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.3E-10.^Show 0.0000000001330839194710102800
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.95 in 1.3E-8% of random cases. Said differently, if you correlated 7,514,055,823 random variables^Note You don't actually need 7 billion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 19 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 19 because we have two variables measured over a period of 20 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.88, 0.98 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!

All values for the years included above: ^Note If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Butter consumption (Pounds per person)	4.4	4.5	4.5	4.5	4.7	4.7	5	5	4.9	5.4	5.5	5.5	5.5	5.6	5.7	5.7	6	6.2	6.3	6.5
Novo Nordisk's stock price (NVO) (Stock price)	2.03	1.46	2.05	2.7	2.84	4.22	6.5	5.19	13.04	22.13	23.66	33.13	36.92	42.55	57.79	36.23	54.49	46.13	58.31	71.19

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."

# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([4.4,4.5,4.5,4.5,4.7,4.7,5,5,4.9,5.4,5.5,5.5,5.5,5.6,5.7,5.7,6,6.2,6.3,6.5,])
array_2 = np.array([2.03,1.46,2.05,2.7,2.84,4.22,6.5,5.19,13.04,22.13,23.66,33.13,36.92,42.55,57.79,36.23,54.49,46.13,58.31,71.19,])
array_1_name = "Butter consumption"
array_2_name = "Novo Nordisk's stock price (NVO)"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Butter consumption
Line chart for only Novo Nordisk's stock price (NVO)
AI-generated correlation image
The spurious research paper: Spreadin' Butter, Movin' the Market: Exploring the Correlation Between Butter Consumption and Novo Nordisk's Stock Price

View another random correlation

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Big thanks for reviewing!

Correlation ID: 2003 · Black Variable ID: 557 · Red Variable ID: 1555


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